BEGINNER • SQL Fundamentals
Sprint: improve lineage tracking #22
This lesson focuses on improve lineage tracking for a inventory management environment. You will use: python -m venv venv | python etl_script.py | CREATE TABLE events (id SERIAL PRIMARY KEY). The content is designed for practical data engineering execution.
Code Example
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("inventory management").getOrCreate()
df = spark.read.parquet("s3://bucket/raw/")
df.filter("event_type = 'purchase'").write.mode("overwrite").parquet("s3://bucket/processed/")
# Objective: improve lineage trackingCommands & References
- python -m venv venv
- python etl_script.py
- CREATE TABLE events (id SERIAL PRIMARY KEY)
Lab Steps
- Prepare environment with: python -m venv venv
- Design or modify the data pipeline for the scenario.
- Validate data quality and document lineage.
- Propose one optimization for production.
Exercises
- Add one data quality check.
- Implement one incremental loading pattern.
- Write a rollback procedure for this pipeline.